Postdoctoral Fellow (Liu Jianjun’s Lab)
Position Code: SC10345
We are looking for motivated candidate who will be working in computational cancer genomics in Dr Liu Jianjun’s lab. Our group uses computational and statistical methods in studying tumor heterogeneity and progression focusing on genomic changes in a typical tumor at the time of diagnosis as well as how tumors evolve and the dynamics of tumor evolution under treatment conditions. The candidate will be responsible for the coordination and management of the genomic projects of the multidisciplinary study. He/she will also be involved in a large-scale international study on hepatocellular carcinoma, which utilises various types of patient samples and employs multi-omics approaches including bulk tumor next-generation sequencing (NGS), single cell NGS, cfDNA NGS, CyTOF and metabolomics.
- PhD in Computational Biology or a quantitative background (e.g. Statistics, Physics, Engineering), or Biomedical-related disciplines with a strong evidence of computational experience.
- Experience with large-scale bioinformatics analysis (including, but not restricted to next-generation sequencing, transcriptomic analysis and disease modelling).
- Proficient in R or Python, good knowledge of Unix shell and cloud computing.
- Possess excellent analytical, technical and problem-solving skills.
- Well organised and detail oriented.
- Ability to coordinate diverse groups of people.
- Excellent written and verbal communication skills.
- Good team player and fast learner.
- Project management experiences will be advantageous.
Those interested to apply, please send your application including CV, publication list and names of three referees to Jianjun Liu (email@example.com
) and cc firstname.lastname@example.org
The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice.
* We regret that only shortlisted candidates will be notified.